Results 91 to 100 of about 116,234 (262)

An Improved Fault Detection Method based on HSMM: Application to a Chemical Process

International Journal of Prognostics and Health Management
This paper proposes a fault detection method for multivariate statistical process control. The proposed method combines the Forward-Backward Hidden Semi-Markov Model (HSMM) and Principal Component Analysis (PCA). A stochastic automaton was used for multi-
Lestari Handayani, Pascal Vrignat, Frédéric Kratz   +2 more
doaj   +1 more source

Learning Controllers for Reactive and Proactive Behaviors in Human-Robot Collaboration

Frontiers in Robotics and AI, 2016
Designed to safely share the same workspace as humans and assist them in a variety of tasks, the new collaborative robots are targeting manufacturing and service applications that once were considered unattainable.
Sylvain eCalinon, Leonel eRozo, João eSilvério, Darwin Gordon Caldwell   +3 more
doaj   +1 more source

Statistical identification with hidden Markov models of large order splitting strategies in an equity market

, 2010
Large trades in a financial market are usually split into smaller parts and traded incrementally over extended periods of time. We address these large trades as hidden orders.
Lillo, Fabrizio, Mantegna, Rosario N., Vaglica, Gabriella   +2 more
core   +1 more source

Health Assessment and Prognostics Based on Higher Order Hidden Semi-Markov Models [PDF]

, 2022
Ying Liao, Yisha Xiang, Min Wang
openalex   +1 more source

Bayesian Nonparametric Hidden Semi-Markov Models

, 2012
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data.
Johnson, Matthew J., Willsky, Alan S.
core  

拡張隠れセミマルコフモデルによる複数系列データモデリングとデータ収集・管理手法 [PDF]

, 2018
In recent years, with the development of devices and the development of data aggregation methods, data to be analyzed and aggregating methods have been changed.
Hiromi Narimatsu, 成松 宏美
core   +2 more sources

Inference in Hidden Markov Models with Explicit State Duration Distributions

, 2012
In this letter we borrow from the inference techniques developed for unbounded state-cardinality (nonparametric) variants of the HMM and use them to develop a tuning-parameter free, black-box inference procedure for Explicit-state-duration hidden Markov ...
Dewar, Michael, Wiggins, Chris, Wood, Frank   +2 more
core   +2 more sources

Localizing the latent structure canonical uncertainty: Entropy profiles for hidden Markov models [PDF]

, 2007
Ce rapport concerne l'inférence sur les états de modèles de Markov cachés. Ces modèles se fondent sur des états non observés, qui ont en général une interprétation, dans le contexte d'une application donnée. Ceci rend nécessaire la conception d'outils de
Durand, Jean-Baptiste, Guédon, Yann
core  

hsmm — An R package for analyzing hidden semi-Markov models

Computational Statistics & Data Analysis, 2010
Hidden semi-Markov models are a generalization of the well-known hidden Markov model. They allow for a greater flexibility of sojourn time distributions, which implicitly follow a geometric distribution in the case of a hidden Markov chain. The aim of this paper is to describe hsmm, a new software package for the statistical computing environment R ...
Bulla, Jan, Bulla, Ingo, Nenadic, Oleg
openaire   +2 more sources

Duration and Interval Hidden Markov Model for Sequential Data Analysis

, 2015
Analysis of sequential event data has been recognized as one of the essential tools in data modeling and analysis field. In this paper, after the examination of its technical requirements and issues to model complex but practical situation, we propose a ...
Kasai, Hiroyuki, Narimatsu, Hiromi
core   +1 more source